Dents in the Mirror: A Novel Probe of Dark Matter Substructure in Galaxy Clusters from the Astrometric Asymmetry of Lensed Arcs
Derek Perera, Daniel Gilman, Liliya L. R. Williams, Liang Dai, Xiaolong Du, Gregor Rihtarsic, Joaquin Becerra-Espinoza, Allison Keen

TL;DR
This paper introduces a new statistical method using astrometric asymmetry of lensed arcs to constrain dark matter substructure in galaxy clusters, demonstrating its effectiveness with mock and real data.
Contribution
The authors develop a novel approach combining semi-analytic modeling and Bayesian computation to estimate dark matter subhalo fractions from lensing asymmetries.
Findings
Method reliably recovers simulated subhalo fractions within 68% CI in most cases.
Application to real data yields upper limits consistent with CDM predictions.
Optimal for large samples of well-observed arcs, especially with JWST.
Abstract
Astrometric perturbations of lensed arcs behind galaxy clusters have been recently suggested as promising probes of small-scale () dark matter substructure. Populations of cold dark matter (CDM) subhalos, predicted in hierarchical structure formation theory, can break the symmetry of arcs near the critical curve, leading to positional shifts in the observed images. We present a novel statistical method to constrain the average subhalo mass fraction () in clusters that takes advantage of this induced positional asymmetry. Focusing on CDM, we extend a recent semi-analytic model of subhalo tidal evolution to accurately simulate realistic subhalos within a cluster-scale host. We simulate the asymmetry of lensed arcs from these subhalo populations using Approximate Bayesian Computation. Using mock data, we demonstrate that our method can reliably recover…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
